Piyushimita Thakuriah

Evaluating pedestrian crashes in areas with high low-income or minority populations.

In this paper, we present an analysis of the relationship between pedestrian-vehicle crashes and characteristics of areas with high low-income and minority populations in the Chicago metropolitan area (also called environmental justice or EJ areas in the United States). While related research has indicated that pedestrian crashes occur more frequently in these areas than in non-EJ areas, this paper attempts to relate the incidence to environmental characteristics and behavioral factors through a better understanding of the contributing factors present in crash occurrences in EJ versus non-EJ areas. Specially constructed small-area factors from a Spatial Decision Support System (SDSS) are used to explain pedestrian-vehicle crashes. Using a Poisson model that corrects for underreporting, we find that pedestrian crash incidents in EJ areas are related to variables of exposure (including the suitability of the area for walking and transit accessibility), crime rates, transit availability, and general population demographics such as income and presence of children. Results suggest that it may be necessary to better incorporate a safety perspective or measures of safety improvements in pedestrian and transit improvements and expansion programs within EJ areas.

Analysis of Transit Quality of Service and Employment Accessibility for the Greater Chicago, Illinois, Region

A variety of transit decision support tools have been developed in the Chicago, Illinois, metropolitan area in recent years, including the Regional Transportation Asset Management System of the Regional Transit Authority and the Spatial Decision Support System of the Urban Transportation Center at the University of Illinois at Chicago. Although the Chicago metropolitan area has a variety of public transportation services, the quality of service available in an area and the extent to which transit allows area residents to access employment opportunities spread out across the six-county region vary substantially. This paper focuses on a spatial analysis of the variations of local transit service quality indicators as well as a composite regional employment accessibility measure. It explores the quality of the transit system in the Chicago region through a set of supply- and demand-side indicators at the census tract level. The supply-side indicators include a composite index of transit availability and frequency and transit station asset information. The demand-side measures include the computation of the regional employment accessibility index using a gravity model and transit travel times from travel demand models. A series of these indicators is mapped over the Chicago region at the census tract level. The paper also ranks census tracts on the local transit measures, as well as on the regional transit-based employment accessibility measures, and identifies those areas that are well off and worst off in regard to both types of indexes. The paper draws policy conclusions emanating from each of these categories.

Will Psychological Effects of Real-Time Transit Information Systems Lead to Ridership Gain?

This paper examines whether the psychological effects of real-time transit information on commuters will lead to a gain in transit ridership. A conceptual model, which posits a simultaneous structure among psychological and behavioral constructs, was developed on the basis of cognitive models of behavior. Path analysis was used to analyze such a process. A detailed stated preference survey for Chicago commuters composed the data-gathering approach. The analysis results showed that real-time transit information systems might achieve the goal of increasing transit ridership through their psychological effects on commuters. The results indicated that the provision of real-time transit information might serve as an intervention to break current transit nonusers’ travel habits and in consequence increase the mode share of transit use. Moreover, the results of this study suggest that real-time transit information may be more successful in increasing transit ridership if combined with facilitating programs that enhance commuters’ opportunities to be exposed to such systems before using them.

Effect of Residential Location and Access to Transportation on Employment Opportunities

Women who have been on public assistance need to obtain and maintain steady employment because they stand to lose their public benefits and also because it is the only way out of poverty. Although the sociodemographic and general economic influences on job retention have been examined in the literature, the effects of transportation and of place of residence in a metropolitan area vis-à-vis entry-level job locations have not been studied systematically. Four sets of factors—transportation, location, sociodemographic, and family effects—are examined for their effect on job retention. In particular, it was found that employment security for female welfare clients or former clients does not come from job retention (i.e., tenure with the same employer) but from “employment retention” (i.e., jobs with different employers, possibly with a trend toward upward mobility). The effects of transportation and location on job and employment retention are complex. Although access to a vehicle is important for increasing employment retention, even more important is the number of job opportunities accessible by private vehicle or public transit within a tolerable travel time. Female welfare clients who retain a job longer and hold more jobs within a 2-year period are more likely to live in subareas of the metropolitan area with greater access to jobs within reasonable travel times; the competition for those jobs from other low-income individuals is low. Furthermore, female welfare clients with a high school diploma, when given the appropriate accessibility and location opportunities, enjoy increased job retention.

Analysis of Variations in Vehicle Ownership Expenditures

There is significant concern about the high cost of vehicle ownership, although several authors have acknowledged in the literature that owning and operating a vehicle have accessibility benefits. This paper uses Consumer Expenditure Survey data to explore vehicle ownership expenditures of American households. Differences in vehicle ownership expenditures among urban and rural households are estimated in different regions of the United States, controlling for socioeconomic, demographic, life cycle, and other household factors. First, patterns in vehicle ownership expenses are examined over a year. Three models of expenditures for vehicle ownership are estimated: the first model is estimated by ordinary least squares, the second is a Tobit model estimated to take into account zero expenditures on vehicles by a segment of households during the survey year, and the third model is a two-stage sample selection model that explicitly models first the household vehicle ownership decision and then, given that firs...

Estimation of static travel times in a dynamic route guidance system-II

In an earlier paper a method for computing static profiles of link travel times was given. In this paper, the centrality of such profiles for ATIS is examined and the methods given in the earlier paper are applied to actual data. Except for a minor, easily correctable problem, the methods are shown to work very well under real-life conditions.

Big Data and Urban Informatics: Innovations and Challenges to Urban Planning and Knowledge Discovery

Big Data is the term being used to describe a wide spectrum of observational or “naturally-occurring” data generated through transactional, operational, planning and social activities that are not specifically designed for research. Due to the structure and access conditions associated with such data, their use for research and analysis becomes significantly complicated. New sources of Big Data are rapidly emerging as a result of technological, institutional, social, and business innovations. The objective of this background paper is to describe emerging sources of Big Data, their use in urban research, and the challenges that arise with their use. To a certain extent, Big Data in the urban context has become narrowly associated with sensor (e.g., Internet of Things) or socially generated (e.g., social media or citizen science) data. However, there are many other sources of observational data that are meaningful to different groups of urban researchers and user communities. Examples include privately held transactions data, confidential administrative micro-data, data from arts and humanities collections, and hybrid data consisting of synthetic or linked data.

Protecting location privacy: policy evaluation

With the growing trend toward location-based services in transportation, the collection and the use of traveler data have grown rapidly. With the potential for multiagency sharing of data and an increased public-private partnerships, inconsistencies in how data are collected and shared may become of growing concern for users, particularly given the potential sensitivity of locational data. An overall picture of policies relevant to data collection and use in the private locational environment highlights the gaps that may be evident between the privacy recommendations of regulatory and industry guidance agencies and individual company policies. The approach combines policy and content analysis to determine how well identified privacy considerations are reflected in user-oriented privacy policies.

Car Ownership Among Young Adults: Generational and Period-Specific Perspective

An individual-level mixed longitudinal data set with three separate cohorts representing three generations in U.S. society is used to examine how car ownership trends have changed among young adults (18 to 24 years of age) over a 40-year period, from the mid-1960s to the mid-2000s. A multilevel, mixed model for binary car-ownership outcomes was estimated by using maximum likelihood. After controlling for factors relating to sociodemographics, personal life, location, and labor market, individuals in the past generation considered (who were young adults in the late 1990s and early 2000s) were found to be significantly more likely to enter the car market at an earlier age. In contrast to earlier generations, by the time individuals in the last generation cleared the 18- to 24-year window, they were found to have reached car ownership levels that had been predicted by earlier studies to be the saturation levels of car ownership in a society. Minorities made greater progress in rates of car ownership between the late 1960s and the early 1980s compared with nonminorities; however, increases in the rates of car ownership slowed for minorities in the most recent generation. Young adults in urban areas led those in rural areas in the earlier generations on car ownership rates but fell behind their rural counterparts in the last generation considered. Across all three generations, vehicle ownership was lower among the unemployed compared with the employed. The differential between employed and unemployed increased with each successive generation and was almost 30% in the last generation considered.

Transportation Expenditures and Ability to Pay: Evidence from Consumer Expenditure Survey

Data at several levels of aggregation and spatial resolution show that mobility (measured by different outcomes such as vehicle miles traveled and automobile ownership) increases with income. It is equally likely that, in turn, investments in mobility (purchase and operation of private automobiles, consumption of public transportation services) allow greater quality of life in general and the ability to increase ones income. This possibly circular relationship is explored by using the Consumer Expenditure Survey (CEX) data set. Single-equation Tobit models of annual household transportation expenditures are posited with, in the first case, annual before-tax income and, in the second case, annual total household-level expenditures as a proxy for permanent income. With a variety of demographic, community and spatial, economic, family, and life-cycle conditions of the household controlled, it is found that permanent incomes explain mobility investments better than annual incomes. However, mobility investmen...